Triple
T2463458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XLII |
E54586
|
entity |
| Predicate | belongsToNumeralSystem |
P7356
|
FINISHED |
| Object | Roman numeral system |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Roman numeral system | Statement: [XLII, belongsToNumeralSystem, Roman numeral system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToNumeralSystem Context triple: [XLII, belongsToNumeralSystem, Roman numeral system]
-
A.
hasNumberSystem
Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
-
B.
hasArabicNumeral
Indicates that an entity is associated with, represented by, or expressed using an Arabic numeral.
-
C.
notationSystem
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
-
D.
usesRomanNumerals
chosen
Indicates that something represents numbers or sequences using the Roman numeral system rather than standard Arabic digits.
-
E.
hasNumberDistinction
Indicates that a language or system grammatically distinguishes between different numbers (such as singular, plural, dual, etc.) in its expressions.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0b3ea308190a6d8499c2a542c50 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.